Cost-effectiveness implications of GP intervention to promote physical activity: evidence from Perth, Australia

<p>Abstract</p> <p>Background</p> <p>Physical inactivity is a major risk factor for many chronic diseases including diabetes, cardiovascular diseases and some cancers. It is estimated that, in Australia, physical inactivity contributes to 13,500 annual deaths and incurs an annual cost of AU$21 billion to the health care system. The cost of physical inactivity to the Western Australian (WA) economy is estimated to be about AU$ 2.1 billion. Increased burden of physical inactivity has motivated health professionals to seek cost effective intervention to promote physical activity. One such strategy is encouraging general practitioners (GPs) to advocate physical activity to the patients who are at high risk of developing chronic diseases associated with physical inactivity. This study intends to investigate the cost-effectiveness of a subsidy program for GP advice to promote physical activity.</p> <p>Methodology</p> <p>The percentage of population that could potentially move from insufficiently active to sufficiently active, on GP advice was drawn from the Western Australian (WA) Premier's Physical Activity Taskforce (PATF) survey in 2006. Population impact fractions (<it>PIF</it>) for diseases attributable to physical inactivity together with disability adjusted life years (<it>DALYs</it>) and health care expenditure were used to estimate the net cost of intervention for varying subsidies. Cost-effectiveness of subsidy programs were evaluated in terms of cost per <it>DALY </it>saved at different compliance rates.</p> <p>Results</p> <p>With a 50% adherence to GP advice, an annual health care cost of AU$24 million could be potentially saved to the WA economy. A <it>DALY </it>can be saved at a cost of AU$ 11,000 with a AU$ 25 subsidy at a 50% compliance rate. Cost effectiveness of such a subsidy program decreases at higher subsidy and lower compliance rates.</p> <p>Conclusion</p> <p>Implementing a subsidy for GP advice could potentially reduce the burden of physical inactivity. However, the cost-effectiveness of a subsidy program for GP advice depends on the percentage of population who comply with GP advice.</p

A socioeconomic and spatial analysis of obesity in West Virginia: Policy implications

This dissertation integrates both theoretical and empirical insights to facilitate understanding of the current obesity epidemic in WV given heterogeneity in socioeconomic, demographic and built environment characteristics of the state. In meeting this objective, county-level and individual-level health demand analyses using secondary data sources were conducted. County-level obesity differences were studied using spatial and non-spatial random and fixed effects frameworks under a panel data structure. Individual health demand was investigated by recursive estimation of individual health responses to ordered self-assessed health (SAH) in terms of lifestyle choices, socioeconomic, demographic and built environment characteristics using Behavioral Risk Factor Surveillance System (BRFSS) data.;County level findings reveal that, while the percentage of the population with a completed college degree and the number of food stores available per thousand population are negatively and significantly correlated to county prevalence of obesity, mean commuting time, average annual wage and the total number of business establishments per thousand population positively and significantly contribute to obesity. Although there is no evidence for unobserved county fixed effects or serial correlation, empirical and spatial investigations suggest that obesity is a spatially non-random event clustered in certain geographic regions which also have the highest poverty and least education.;The individual health demand analysis shows that the risk of obesity increases at a decreasing rate with per capita income and age. Marginal impacts indicate that as the level of education increases, the probability of being obese decreases by 3%. Physical inactivity increases the risk of being obese by 9%, while smoking reduces the risk of being obese by 14%. Fruit and vegetable consumption lowers the probability of being obese by 2%, while each one-minute increase in commute time raises the probability of being obese by 0.04%. In addition, individuals living in economically distressed counties are less likely to have good health. In general, the overall causes for, and consequences of, obesity are found to be complex and multifaceted.;In terms of policy interventions, educational attainment that raises both human and social capital, as well as changes in the built environment can play a vital role in controlling obesity in West Virginia.;Keywords. obesity, health, random and fixed effects, spatial and built environment characteristics, policy interventions

Obesity Prevention: A Review of the Interactions and Interventions, and some Policy Implications

Obesity is reaching epidemic proportions especially in the developed and, more recently, in the developing world where the problem is compounded by myriad socio-economic, demographic, built and natural environmental factors. This review examines the possible causes, consequences and policy implications using a multilevel, multispectral framework. The causes of obesity clearly are multifaceted and involve numerous interactions. Together with economic incentives, allocation of physical and financial resources to community intervention strategies through educational programs as well as better land use planning would be helpful in promoting healthier and sustainable communities. Towards this goal, we proposed a dynamic and integrated Individual, Social, Economic and Environmental Model (ISEEM) for obesity prevention. The use of an ISEEM framework, involving a strategic combinations of strategies and targeted to the specific circumstances of individual communities and localities could be helpful for obesity prevention in the years to come

The Influence of Socioeconomic and Environmental Factors on Health and Obesity in Rural Appalachia

A recursive system of ordered self assessed health (SAH) and a binary indicator of obesity were used to investigate the impact of socioeconomic and environmental factors on health and obesity in the predominantly rural Appalachian state of West Virginia. Behavioral Risk Factor Surveillance System (BRFSS) data together with county specific socioeconomic and built environment indicators were used in estimation. Results indicate that an individual’s risk of being obese increases at a decreasing rate with per capita income and age. Marginal impacts show that as the level of education attainment increases, the probability of being obese decreases by 3%. Physical inactivity increases the risk of being obese by 9%, while smoking reduces the risk of being obese by 14%. Fruit and vegetable consumption lowers the probability of being obese by 2%, while each hour increase in commuting time raises the probability of being obese by 2.4%. In addition, individuals living in economically distressed counties are less likely to have good health. Intervention measures which stimulate human capital development and better land use planning are essential policy elements to improving health and reducing the incidence of obesity in rural Appalachia

The Impact of County Level Factors on Obesity in West Virginia

A panel estimation of county prevalence of obesity indicates that while the percentage of the population with a completed college degree and the number of food stores available per thousand population are negatively and significantly correlated to county obesity rates, mean commuting time, average annual wage and the total number of business establishments per thousand population positively and significantly contribute to obesity. Educational attainment that raises both human and social capital, as well as changes in the built environment can play a vital role in controlling obesity in West Virginia (WV)

A Spatial Analysis of Obesity in West Virginia

A spatial panel data analysis at the county level examines how individual food consumption, recreational, and lifestyle choices ― against a backdrop of changing demographic, built environment, and policy factors ― leads to obesity. Results suggest that obesity tends to be spatially autocorrelated; in addition to hereditary factors and lifestyle choices, it is also caused by sprawl and lack of land use planning. Policy measures which stimulate educational attainment, poverty alleviation, and promotion of better land use planning and best consumption practices (BCPs) could both reduce obesity and result in sustainable development of regions where obesity is prevalent and the economy is lagging

The Influence of Socioeconomic and Environmental Determinants on Health and Obesity: A West Virginia Case Study

A recursive system of ordered self assessed health together with BRFSS data were used to investigate health and obesity in the Appalachian state of West Virginia. Implications of unobserved heterogeneity and endogeneity of lifestyle outcomes on health were investigated. Obesity was found to be an endogenous lifestyle outcome associated with impaired health status. Risk of obesity is found to increase at a decreasing rate with per capita income and age. Intervention measures which stimulate human capital development, diet-disease knowledge and careful land use planning may improve health and obesity outcomes in Appalachia in particular and rural America in general

How important is the land use mix measure in understanding walking behaviour? Results from the RESIDE study

<p>Abstract</p> <p>Background</p> <p>Understanding the relationship between urban design and physical activity is a high priority. Different representations of land use diversity may impact the association between neighbourhood design and specific walking behaviours. This study examined different entropy based computations of land use mix (LUM) used in the development of walkability indices (WIs) and their association with walking behaviour.</p> <p>Methods</p> <p>Participants in the RESIDential Environments project (RESIDE) self-reported mins/week of recreational, transport and total walking using the Neighbourhood Physical Activity Questionnaire (n = 1798). Land use categories were incrementally added to test five different LUM models to identify the strongest associations with recreational, transport and total walking. Logistic regression was used to analyse associations between WIs and walking behaviour using three cut points: any (> 0 mins), ≥ 60 mins and ≥ 150 mins walking/week.</p> <p>Results</p> <p>Participants in high (vs. low) walkable neighbourhoods reported up to almost twice the amount of walking, irrespective of the LUM measure used. However, different computations of LUM were found to be relevant for different types and amounts of walking (i.e., > 0, ≥ 60 or ≥ 150 mins/week). Transport walking (≥ 60 mins/week) had the strongest and most significant association (OR = 2.24; 95% CI:1.58-3.18) with the WI when the LUM included 'residential', 'retail', 'office', 'health, welfare and community', <it>and </it>'entertainment, culture and recreation'. However, any (> 0 mins/week) recreational walking was more strongly associated with the WI (OR = 1.36; 95% CI:1.04-1.78) when land use categories included 'public open space', 'sporting infrastructure' and 'primary and rural' land uses. The observed associations were generally stronger for ≥ 60 mins/week compared with > 0 mins/week of transport walking and total walking but this relationship was not seen for recreational walking.</p> <p>Conclusions</p> <p>Varying the combination of land uses in the LUM calculation of WIs affects the strength of relationships with different types (and amounts) of walking. Future research should examine the relationship between walkability and specific types and different amounts of walking. Our results provide an important first step towards developing a context-specific WI that is associated with recreational walking. Inherent problems with administrative data and the use of entropy formulas for the calculation of LUM highlight the need to explore alternative or complimentary measures of the environment.</p

Epidemiology and site-specific risk factors for oral cancer

To outline the global epidemiology of oral cancer and recent changes in disease prevalence with the emergence of HPV-induced cancers